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Popular Snowflake and Python Triggers#
Popular Snowflake and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Snowflake#
Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture
Getting Started
1. Create a user, role and warehouse in Snowflake
Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI
We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.
2. Enter those details in Pipedream
Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.
You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.
3. Build your first workflow
Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.
Learn more at Pipedream University
Connect Snowflake#
import snowflake from '@pipedream/snowflake';
export default defineComponent({
props: {
snowflake,
},
async run({ $ }) {
// Component source code:
// https://github.com/PipedreamHQ/pipedream/tree/master/components/snowflake
return this.snowflake.executeQuery({
sqlText: `SELECT CURRENT_TIMESTAMP()`,
binds: [],
});
},
});Overview of Python#
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow
This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
Connect Python#
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}Trusted by 1,000,000+ developers from startups to Fortune 500 companies